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This paper presents a novel framework for cyberbullying detection using hybrid models that integrate machine learning and natural language processing techniques. It compares eleven classification methods, including traditional machine learning and shallow neural networks, on two real-world datasets, achieving high accuracy and F1-scores. Key findings indicate that bidirectional neural networks and attention models excel in classification performance, while Logistic Regression performs best among traditional
- Author
- glsa.galam.coc
- Language
- EN